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» Decision Trees for Functional Variables
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AMAI
2004
Springer
14 years 1 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
ICIC
2009
Springer
14 years 2 months ago
Function Sequence Genetic Programming
Genetic Programming(GP) can obtain a program structure to solve complex problem. This paper presents a new form of Genetic Programming, Function Sequence Genetic Programming (FSGP)...
Shixian Wang, Yuehui Chen, Peng Wu
WSC
2008
13 years 10 months ago
The mathematics of continuous-variable simulation optimization
Continuous-variable simulation optimization problems are those optimization problems where the objective function is computed through stochastic simulation and the decision variab...
Sujin Kim, Shane G. Henderson
ICML
2006
IEEE
14 years 8 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
UAI
1997
13 years 9 months ago
Nonuniform Dynamic Discretization in Hybrid Networks
We consider probabilistic inference in general hybrid networks, which include continuous and discrete variables in an arbitrary topology. We reexamine the question of variable dis...
Alexander V. Kozlov, Daphne Koller